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LLMs in HR analytics: how it helps HR make better decisions

As an HR professional, you need to be both strategic and agile in your decision-making. With the integration of advanced technologies, such as large language models (LLM), HR analytics is undergoing a transformation. You now have the ability to get valuable insights to drive better decisions. Let’s look at how LLM can factor into your workflow – and no, you don’t have to be a data geek or computer expert to make it happen!

llms in hr analytics

Wait – what are LLMs in the first place?

OK, let’s define LLMs. Basically, LLMs are AI-based models designed to understand, generate, and process human language, enabling more efficient and accurate analysis of text data. In layperson’s terms, it takes a whole pile of information and packages it nicely for you so you can have a clearer view of what’s happening in your organization.

Got that? Don’t stress if it’s not quite ‘there’ for you yet – stay with us and it will eventually click.

The benefits of LLMs in HR analytics

There are many advantages to incorporating LLM into HR analytics, but it all boils down to one thing: it ultimately helps you make well-informed choices – especially in alignment with business objectives. Not only does it make you work smarter, it also gets you a seat at the boardroom table when it comes to overall strategy. That’s always a good thing.

Now, let’s delve into the specific advantages and the different aspects of each one.

1. Enhances data analysis and interpretation

Traditional analysis methods often struggle to process and interpret complex human language, making it difficult to identify meaningful patterns and trends. However, LLMs excel at understanding and processing human language, especially what was previously large volumes of unstructured text data.

Because LLMS can understand and process that data – and ultimately build reports on them – you can gain incredible insights that were previously hidden or inaccessible.

There are many different ways LLMs can do this. Let’s look at a few:

Sentiment analysis

LLMs can perform sentiment analysis on employee feedback, surveys, and even informal communication channels like email or chat platforms – there are even tools out there that can help you do this, such as Erudit. By identifying and quantifying the emotional tone in these texts, you can gain a deeper understanding of your employees’ feelings and concerns.

Now that you can gauge the ‘temperature in the room’, you can address issues more effectively and create a work environment that fosters positivity and satisfaction. What’s more, you can also measure the impact of initiatives that you’ve introduced in response to these analyses – and adjust accordingly.

Identifying key themes and topics

Similarly to above, you can use LLMs to extract key themes and topics from large datasets, such as employee feedback or exit interviews.

This helps you identify recurring patterns and areas that require attention, allowing you to prioritize your HR initiatives and allocate resources more strategically.

Natural language generation

LLMs can also generate human-like text based on the patterns and trends they identify. This capability can be used to create summaries of complex datasets, draft reports, or even suggest potential actions and interventions based on the insights they uncover.

By automating these tasks, you can save time and focus on higher-level strategic decision-making.

Multilingual support

One significant advantage of LLMs is their ability to work with multiple languages. If your organization operates across multiple countries or employs a multilingual workforce, LLMs can help you analyze and interpret data across various languages, ensuring that your insights are comprehensive, inclusive and uniform.

Text data is nearly impossible to measure on its own. There are multiple emails, text messages, online chats, forums, surveys, etc., that each contain massive repositories of information. It’s all very nascent data too – but you’d love to be able to have someone (or something) to look at all this data and pull up some interesting insights that help guide your work.

Now, let’s imagine that you or another HR team member were to go through it all rather than using technology to help you along. One person may see something in that data that another person wouldn’t. And that means a risk of bias and misinterpretation.

Which brings us to the next benefit of using LLMs in your workflow.

2. Reduces bias in recruitment and talent management

Bias is always a consideration in recruitment and talent management. We can train ourselves to overcome unconscious bias in workflows, but there’s human limitations here. LLMs aren’t hampered by human limitations. You can use LLMs to mitigate bias through automating aspects of the hiring process and introducing a more data-driven process. This ultimately creates a more equitable and inclusive work environment.

Let’s look at the different ways in which it can do this.

Resume screening

LLMs can be utilized to screen resumes based on objective criteria, such as skills, experience, and qualifications, and parse them so you can see exactly what you need to see to help make a decision. These technologies already exist in spades – including in Workable.

By removing subjective human judgment from the screening process, LLMs can help reduce and even eliminate biases that may arise from factors including gender, race, or age. This results in a more diverse candidate pool, ensuring fairness and equal opportunities across the board.

Job descriptions and advertisements

Before you publish job descriptions, you can have LLMs analyze them to identify and remove biased language or phrasing that may unintentionally deter certain candidates. By using neutral language and emphasizing the essential skills and qualifications, you can attract a wider range of applicants.

Again, there are numerous technologies that help you do this. One such example is Ongig.

Interview questions and assessments

LLMs can also be employed to develop interview questions and assessments that are both job-relevant and unbiased.

This ensures that all candidates are evaluated based on their skills and abilities rather than subjective factors including how well they get along with the hiring manager in an interview.

Performance evaluation

You can also use LLM technologies to help reduce biases in performance evaluations by analyzing employee performance data and identifying objective criteria for assessment. In doing this, you can standardize metrics for evaluating employees in your company.

This ensures that promotions, raises, and other career development opportunities are based on merit rather than personal biases.

Succession planning and mentorship

It’s also crucial to have an unbiased approach to analyzing the skills, experiences, and potential of your employees. LLMs can help you identify high-potential individuals for succession planning and mentorship programs, increasing overall business performance in the long run.

Opportunities for growth and advancement are then equally accessible to all employees regardless of background or personal connections – the latter of which can lead to flawed decision making.

3. Improves employee engagement and retention

Employee engagement and talent retention are two crucial factors in business success. When your top people are motivated to do their very best day in and day out, and they’re in it for the long haul, that means greater productivity and a stronger employer brand.

When you incorporate LLMs into your HR analytics strategy, you’re better able to understand and address the factors that impact employee engagement and retention. Consequently, you can develop targeted interventions that cater to the unique needs of your workforce, resulting in a more satisfied and committed team.

Analyzing employee feedback

We discussed this to a degree above – LLMs can process large volumes of employee feedback from numerous sources including survey responses, town hall discussions, and team/one-on-one meetings.

You’ll be able to identify trends and recurrent themes in this feedback and gain a stronger understanding of the factors that drive dissatisfaction and satisfaction in your employees. And you can then act accordingly.

Customized employee experience

LLMs can also help you build tailored employee experiences that cater to individual preferences, strengths, and development needs.

These include personalized learning and development opportunities, flexible working arrangements, or targeted rewards and recognition programs.

Identifying drivers of engagement

You can dig deeper into that feedback and see what actually motivates employees. Are you seeing more positive feedback after a specific initiative such as a company-wide retreat or the introduction of a bonus system for higher-performing employees?

There are some initiatives that work and some that don’t – LLMs can help you better ‘listen’ to employees and see what drives engagement within your organization, and what motivates and inspires individual teams. You can then develop targeted strategies that lead to increased productivity and reduced turnover.

Early detection of employee burnout

It’s important to monitor for signs of impending burnout and preempt that before it happens. Employee burnout can be costly for employers, so early detection is crucial.

By analyzing patterns in employee communication, behavior and performance, LLMs can help you identify those warning signs of disengagement. When you have that information readily displayed in front of you, you can proactively address potential issues and triggers, and offer support and interventions to help employees regain their motivation and enthusiasm for their work.

Building a stronger organizational culture

Workplace culture is multifaceted and can play a role in the success or failure of a company. With LLM technology at your disposal, you can analyze the cultural attributes of your organization by processing data from various sources, such as employee feedback, internal communications and even social media activity.

By understanding the strengths and weaknesses of your organizational culture, you can implement initiatives that reinforce positive values, foster collaboration, and promote a sense of shared purpose among your team members.

By leveraging LLMs to improve employee engagement and retention, you can create a work environment that nurtures satisfaction, commitment and high performance. The ability to analyze employee feedback, customize employee experiences, identify drivers of engagement, detect early signs of burnout, and build a stronger organizational culture empowers you to retain top talent and drive long-term business success.

4. Streamlines performance management

Your performance management processes are another area that can benefit from the use of LLMs. You can get a more comprehensive understanding of individual employee performance.

By analyzing various factors, such as communication patterns and task completion rates, LLMs can help you identify strengths, areas for improvement and potential skill gaps.

With this, you can create targeted and effective development plans that support your employees’ overall performance and growth.

Objective performance metrics

LLMs can analyze performance data and generate objective metrics that provide a consistent basis for evaluating your team members.

With data-driven insights at the ready, you can minimize subjective biases and ensure that promotions, raises and other career development opportunities are based on merit and properly aligned with your organization’s goals.

Real-time performance feedback

You can also use LLM tech to monitor employee performance in real time, providing you with to-the-minute information on your team members’ progress and achievements. You can distribute these insights to team managers and department heads who can then utilize this to best manage their teams with feedback and recognition.

That ultimately creates a culture of continuous improvement and clarity on areas ripe for improvement.

Identifying skill gaps and development needs

When you have clear insights on employee performance, you can also use LLMs to identify skills gaps and needs within your company structure.

You can act on these data through learning & development programs, creating new job roles, and even restructure teams so that workflows are better optimized and company goals are met.

Enhancing collaboration and teamwork

Work processes often involve collaboration and communication between colleagues.

There’s a lot of dynamics going on there, and by better understanding how team members interact and work together, you can start to implement targeted interventions to promote effective collaboration, enhance teamwork and drive collective performance.

Agile performance management

We’re in a time where a year-over-year business strategy is no longer applicable. What’s working in Q1 doesn’t necessarily work in Q2, and this means business agility is crucial. This means more agile performance management that focuses on continuous learning, development and adaptation.

Empowering team members through shifting business needs gives them better ownership of their performance and growth.

5. Builds predictive analytics for strategic workforce planning

Predictive analytics are crucial to forecasting workforce trends and identifying risks and opportunities. You already have plenty of historical data in your system that’s ripe for analysis – and that data-crunching can be done through LLMs.

The resulting insights – far more than organic analysis can get you – will help you make more concrete decisions related to talent acquisition, retention and optimization.

This helps you get ahead of anticipated shifts and creates a more proactive culture in the workplace. Let’s look at the ways in which learned language technologies can support you in predictive analytics.

Workforce demand forecasting

You can analyze historical and real-time data to predict future workforce demand, helping you identify the skills and competencies your organization will require in the near future to achieve its strategic goals.

You can update recruitment strategy accordingly so that you always have the right people in the right place at the right time.

Employee retention and turnover prediction

By analyzing factors such as employee engagement, performance and job satisfaction, you can identify indicators pointing to an increased risk of turnover – and in turn, implement targeted interventions to retain top talent.

The cost benefit of this is clear – hiring and turnover are expensive in many different ways, and you want to do what you can to preempt that.

Succession planning and leadership development

Who are the great leaders in your organization? Some are clear on the surface, but others aren’t necessarily so clear. It’s well-regarded that a high performer doesn’t necessarily equate to a great manager, and vice versa.

LLMs can help you identify those high-potential individuals in your organization who are well-suited for leadership roles, and those who are more suited to be individual contributor stars. You can use these insights to build succession plans and leadership development initiatives to ensure a strong pipeline of future leaders that carry your business to the next level.

Talent mobility and internal talent market

Internal mobility is one way to mitigate the risks of turnover. It effectively keeps your talent engaged through renewed opportunity and continued development, plus someone already familiar with your company and its systems is far more valuable to you than someone coming in from outside.

With emerging LLM technology and the resulting predictive analytics, you can match employees with roles and projects best suited to their interests and capabilities.

Workforce risk assessment

We’ve covered this extensively above – identifying risks within your workforce such as skills gaps, high attrition rates and insufficient leadership is crucial. Even more so is action in response – and better yet, proactive actions to get ahead of anticipated changes so you can mitigate and even remove impact from your overall performance as a company.

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LLMs in HR analytics: you can start now

Ultimately, you have numerous opportunities with the integration of LLMs into HR analytics. You can enhance data analysis and interpretation, reduce bias, streamline performance management and predict possible outcomes – leading to longer-term business successes on the back of informed, data-driven decisions.

So, how do you get started in that direction? We’ll give you these quick tips to get you off on the right foot:

First, evaluate your organization’s needs. Assess the specific challenges and opportunities within your HR processes to determine where LLMs can have the greatest impact. This can involve discussions across the company, with individual managers and the C-suite, and aligning your HR work with organizational priorities.

Start small – and then scale up. You don’t have to start a revolution. Kick things off with a pilot project that targets a specific area of your HR strategy, such as sentiment analysis or resume screening. Then once you’ve got that nailed down, gradually expand to other areas as you gain confidence and experience.

Collaborate with experts. You don’t have to be the expert from day one. Partner with data scientists, AI specialists and HR tech vendors to ensure that you are leveraging the most advanced and appropriate LLM tools for your organization’s needs.

Invest in training and development. Everyone’s got to start from somewhere and they’re much more able to succeed once they have the know-how. So, equip your HR team with the knowledge and skills necessary to effectively utilize LLMs and interpret the insights they generate.

Monitor and refine. Nothing you do is useful unless you are consistent with what you’re doing over the long term. That’s why you need to regularly track performances and outcomes of your LLM-driven initiatives so you can make adjustments as needed to ensure its ongoing effectiveness.

The power of LLMs in your HR analytics is limitless. But be thoughtful and pragmatic as you approach it. Your organization has unique needs and challenges. You want to harness the potential of LLMs as much as you can to create a more efficient, equitable, and agile workforce that is well-prepared to navigate the complexities of the modern business landscape.

Even with the advent of technology, your brain is still needed to ensure the business ship stays afloat and continues to be steered in the right direction. You are still needed!

Frequently asked questions

What are learned language models (LLMs) and how are they relevant to HR analytics?

LLMs are machine learning models that are trained to understand natural language. They can be used in HR analytics to analyze large volumes of data, identify trends, and generate insights to inform decision-making.

How can LLMs improve the recruitment process?

LLMs can be used to automate various recruitment tasks such as resume screening and candidate scoring, saving time and reducing bias. They can also analyze job postings and company data to help create targeted recruitment strategies that attract the best talent.

What are some ways LLMs can improve employee engagement and retention?

LLMs can help analyze employee feedback, identify drivers of engagement, and detect early signs of burnout. They can also be used to build tailored employee experiences, develop targeted interventions, and identify skill gaps and development needs.

How can LLMs improve performance management processes?

LLMs can help identify strengths, areas for improvement, and potential skill gaps, enabling the creation of targeted and effective development plans. They can also generate objective performance metrics, monitor employee performance in real time, and enhance collaboration and teamwork.

How can LLMs be used for predictive analytics in strategic workforce planning?

LLMs can be used to analyze historical and real-time data to predict future workforce demand, identify indicators pointing to an increased risk of turnover, and identify high-potential individuals for leadership roles. They can also help match employees with roles and projects best suited to their interests and capabilities.

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